Cloud-Based AI Healthcare Delivery for Providence St. Joseph Health

The combination of artificial intelligence
with cloud-based computing offers a lot of promise for commercial applications.
Providence St. Joseph Health based in Renton, WA has taken steps to implement a
healthcare delivery system that incorporates HL7’s Fast Healthcare
Interoperability Resources (FHIR) to do the processing of data sources from a
secure Microsoft Azure-based cloud server. FHIR uses theoretical and logical
models to provide a system for the exchange of data among healthcare
applications. Microsoft’s Azure server enables the use of AI and machine
learning to quickly sift through large volumes of collected data to generate
useful information.

Providence St. Joseph Health is not the
first company to adopt a Microsoft cloud server for use in its health facility.
Rush Medical Center announced last month that they had embraced the use of
Google Cloud to help in the delivery of their medical services. By taking their
unstructured client data stored on their proprietary SNOMED CT system, and
processing it using Google Cloud and Maven Wave, the company was able to
generate actionable insights which personnel could apply to their clients in
real time.

Combining New Technology with Existing Architecture

The solution to most problems in healthcare
is access to enough information to make a diagnosis. Through the use of AI and
cloud servers, medical facilities make it much easier for their personnel to
get pertinent data that affects a particular user or group of users. Rush
Medical Center’s application used AI in the form of natural language processing
(NLP) to administer cancer screenings for early detection, to verify the
completion of medical physicals, and to raise the level of their clinical
documentation.

The idea of combining existing siloed data
with the processing power of artificial intelligence opens the door to a lot of
possibilities for the medical fraternity. Insights can be generated not just
from localized data, but, thanks to the cloud server, from data collected from
different areas of the country. Big data thrives on having more data points to
work with and produces better results with larger pools of data. As more
companies adopt cloud computing, the pool of available public data (and by
extension the accuracy of results) is likely to get better.